๐”– Bobbio Scriptorium
โœฆ   LIBER   โœฆ

Geometrical fuzzy clustering algorithms

โœ Scribed by Michael P. Windham

Publisher
Elsevier Science
Year
1983
Tongue
English
Weight
564 KB
Volume
10
Category
Article
ISSN
0165-0114

No coin nor oath required. For personal study only.

โœฆ Synopsis

Fuzzy clustering algorithms are a basic tool for cluster analysis. Among these. the geometrical fuzzy clustering algorithms arc used when the clustering problem can he viewed as trying to find linear or ellipsoidal concentrations in data. This paper provides a theoretical framework in which currently used geometrical fuzzy clustering algorithms hccomc special Casey Also. a family of functions called feasible arc defined which can be used to construct <uch algorithms and convcrgencc results arc ohtaincd.

๐Ÿ“œ SIMILAR VOLUMES

Fuzzy clustering with evolutionary algor
Fuzzy clustering with evolutionary algorithms
โœ Frank Klawonn; Annette Keller ๐Ÿ“‚ Article ๐Ÿ“… 1998 ๐Ÿ› John Wiley and Sons ๐ŸŒ English โš– 220 KB ๐Ÿ‘ 1 views

Objective function-based fuzzy clustering aims at finding a fuzzy partition by optimizing a ลฝ . function that evaluates a fuzzy assignment of a given data set to clusters that are characterized by a set of parameters, the so-called prototypes. The iterative optimization technique usually requires th

A local geometrical properties applicati
A local geometrical properties application to fuzzy clustering
โœ Antonio Flores-Sintas; JosรฉM. Cadenas; Fernando Martin ๐Ÿ“‚ Article ๐Ÿ“… 1998 ๐Ÿ› Elsevier Science ๐ŸŒ English โš– 779 KB

Possibilistic clustering is seen increasingly as a suitable means to resolve the limitations resulting from the constraints imposed in the fuzzy C-means algorithm. Studying the metric derived from the covariance matrix we obtain a membership function and an objective function whether the Mahalanobis